Mahotas – Transforming image using Daubechies wavelet

0 0 1 minute read

In this article we will see how we can transform image using daubechies wavelet in mahotas. In general the Daubechies wavelets are chosen to have the highest number A of vanishing moments, (this does not imply the best smoothness) for given support width 2A. There are two naming schemes in use, DN using the length or number of taps, and dbA referring to the number of vanishing moments. So D4 and db2 are the same wavelet transform.
In this tutorial we will use “luispedro” image, below is the command to load it.

mahotas.demos.load('luispedro')

Below is the luispedro image

In order to do this we will use mahotas.daubechies method

Syntax : mahotas.daubechies(img, ‘D8’)
Argument : It takes image object and string i.e one of ‘D2’, ‘D4’, … ‘D20’ as argument
Return : It returns image object

Note : Input image should be filtered or should be loaded as grey
In order to filter the image we will take the image object which is numpy.ndarray and filter it with the help of indexing, below is the command to do this

image = image[:, :, 0]

Example 1:

Python3

# importing various libraries
import numpy as np
import mahotas
import mahotas.demos
from mahotas.thresholding import soft_threshold
from matplotlib import pyplot as plt
from os import path
 
# loading image
f = mahotas.demos.load('luispedro', as_grey = True)
 
# making ply gray
plt.gray()
 
# showing image
print("Image")
plt.imshow(f)
plt.show()
 
# Transform using D8 Wavelet to obtain transformed image t
t = mahotas.daubechies(f, 'D8')
 
# showing transformed image
print("Transformed Image")
plt.imshow(t)
plt.show()

Output :

Example 2:

Python3

# importing required libraries
import mahotas
import numpy as np
from pylab import imshow, show
import os
 
 
# loading image
img = mahotas.imread('dog_image.png')
 
# filtering image
img = img[:, :, 0]
 
# showing image
print("Image")
imshow(img)
show()
 
     
# Transform using D8 Wavelet to obtain transformed image t
t = mahotas.daubechies(img, 'D8')
 
# showing transformed image
print("Transformed Image")
imshow(t)
show()